rich-ramsey.github.io/talks/sbs-retreat-25/
Aim: Provide a relevant context and framework for thinking about data analysis and statistics.
Disclaimer: I’m not a statistician. I’m not a statistician. I’m not a …
Image from: https://danawanzer.github.io/stats-with-jamovi/
My undergrad and postgrad stats classes looked like this:
Each week described a different statistical test.
Your job was to choose the right test for a given type of data and run the test (usually via point-and-click in SPSS).
Then you interpret the p-value.
Easy, right?
In the wake of the reproducibility crisis:
I felt the need to become more statistically literate.
Enter:
tidyverse principles (Kurz 2023).A quote from Andrew Gelman (Gelman, 2024):
once the data have been collected, the most important decisions have already been done
All statistical models are fundamentally limited and need to be framed within the wider scientific context (McElreath 2020), such as …:
Before we make inferences and draw conclusions, we should spend more time (Scheel et al. 2021):
\[\color{orange}{Y_i} = \color{blue}{\beta_0} + \color{green}{\beta_1} \color{purple}{X_i} + \color{magenta}{\varepsilon_i}\]
https://lindeloev.github.io/tests-as-linear/
\[\color{orange}{Y_{ij}} = (\color{blue}{\gamma_{00}} + \color{cyan}{u_{0j}}) + (\color{green}{\gamma_{10}} + \color{teal}{u_{1j}})\color{purple}{X_{ij}} + \color{magenta}{\varepsilon_{ij}}\]
Adapted from Kruschke & Liddell, 2018
Statistical reform is important.
But science is not a one-trick pony.
We need more David Bowie.
And thanks to these fine folks:
John Bartlett for his tutorial on reproducible presentations in R (this is solid gold).
Lisa Debruine for sharing lots of example presentations
Website: www.rich-ramsey.com
Github: https://github.com/rich-ramsey